Forecasting term structure of the Japanese bond yields in the presence of a liquidity trap

Albert Tsui, Junxiang Wu, Zhaoyong Zhang and Zhongxi Zheng

Journal of Forecasting, 2023, vol. 42, issue 5, 1205-1227

Abstract: The Nelson–Siegel (NS) model is widely used in practice to fit the term structure of interest rates largely due to its high efficacy in the in‐sample fit and out‐of‐sample forecasting of bond yields. In this paper, we compare forecasting performances of estimated yields from the Nelson–Siegel‐based models and some simpler time series models, using the daily, weekly, and monthly data during a prolong period of liquidity trap in Japan. We find that the out‐of‐sample expanding window forecasts by NS‐based models in general perform less satisfactory than the competitor models. However, the NS‐based models can be useful in forecasting yields over longer horizons and can work well with GARCH‐type structures in modeling the conditional volatility.

Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/for.2952

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:jforec:v:42:y:2023:i:5:p:1205-1227

Access Statistics for this article

Journal of Forecasting is currently edited by Derek W. Bunn

More articles in Journal of Forecasting from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().